Goal misgeneralization is a common failure mode in which an agent behaves competently out of distribution but does not pursue the intended goal. However, we still have a weak understanding of what happens to the intended goal in misgeneralizing agents.
Experiments and Findings
Across three Procgen environments and five robot tasks, we find three distinct forms of policy-goal misalignment:
- functional target substitution, where behavior follows an alternative goal,
- a policy shortcut, where behavior follows a learned action strategy,
- cue competition between intended and proxy goal cues.
We distinguish these regimes by tracing where goal information remains available internally, how strongly it influences the policy, and what role it plays in action selection, and find that the goal is lost at different depths.
Where the goal reaches the decision, as in cue competition, steering redirects the policy to the goal's location, raising intended-goal reach from 16.0% to 95.3%.
Where it reaches the policy but not the decision, only new downstream wiring recovers goal reach, from 31.6% to 84.3% in the environment with the action shortcut.
Where it is inert, neither works.
Conclusion
Our results show that goal misgeneralization is not a single failure of goal representation, but distinct failures of policy alignment at different depths, tightly connected to which recovery works.